Recent digital forensic includes extraction and analyzation of a usage record of a social network service which is widely used. The usage record of the social network service includes a message which is created by a user, uploaded or transmitted multimedia data, positional information, a preference, and connection network information with other people. The forensic analysis for these records is performed by providing a search function of data and suggestion of a relationship between users which are connected through the social network service.
However, due to the usage of a smart phone in which a data communication function and a function as a computer are converged, a frequency of a communication activity using the social network service is sharply increased. Therefore, when the record for the communication activity is extracted to be presented as a list, the size of the list is too much to be able to understand the record at a glance. For this reason, it is difficult to specifically determine a user of communication related to a case, which may contain important information for a digital forensic investigation and comprehend an actual relationship between users who do not have a superficial relationship.
As a known method of comprehending a relationship between speakers in communication, a method that calculates intimacy between an owner of a communication device and a speaker using the communication usage record is suggested. Here, the intimacy is calculated by extracting various communication usage records between the owner and the speaker and calculating the connection strength based on the number of times of communication. When using the above method, it is possible to distinguish a speaker which is intimate with the owner of the device. However, the related art does not provide a method which may comprehend the relationship between two people who do not have a direct communication usage record.
As another related art, a method which represents congruence between personal relationships as a point based on a congruence of interests represented by the users in the social network has been suggested. Here, the congruence is calculated based on a probability that two interests represented by two users coincide with each other. This method represents the similarity between two users who are not directly connected as a point but the determination standard is based on the interest represented by the users. Therefore, the congruence calculated as described above is less accurate as a similarity determining standard which is used for the criminal investigation.
Therefore, a method which improves accuracy in calculating a similarity is demanded.